The political economy of tax laws in the U.S. states

This paper contributes to recent work in political economy and public finance that focuses on how details of the tax code, rather than tax rates, are used to implement redistributive fiscal policies. I use tools from natural language processing to construct a high-dimensional representation of tax code changes from the text of 1.6 million statutes enacted by state legislatures since 1963. A data-driven approach is taken to recover the effective tax code – the set of legal phrases in tax law that have the largest impact on revenues, holding major tax rates constant. Exogenous variation in tax legislation from judicial districts is used to capture revenue impacts that are solely due to changes in the tax code language, with the resulting phrases providing a robust out-of-sample predictor of tax collections. I then test whether political parties differ in patterns of effective tax code changes when they control state government. Relative to Republicans, Democrats use revenue-increasing language for income taxes but use revenue-decreasing language for sales taxes – consistent with a more redistributive fiscal policy – despite making no changes on average to statutory tax rates. These results are consistent with the view that due to their relative salience, changing tax rates is politically more difficult than changing the tax code. ∗PhD candidate (economics), Columbia University. Contact: [email protected]. Web site: elliottash.com. This research is supported by the National Science Foundation. I am grateful to Bentley MacLeod, Wojciech Kopczuk, Suresh Naidu, and Massimo Morelli for support and feedback on this project. Thanks to Yisehak Abraham, Joao de Mello, Mallika Patkar, Aranya Ram, Daniel Reuter, Carol Shou, Anna Vladymyrska, Qing Zhang, Grace Zheng, and Jon Zytnick for helpful research assistance.